Chemical fragment spaces for de novo design

Chemical fragment spaces are combinations of molecular fragments and connection rules. They offer the possibility to encode an enormously large number of chemical structures in a very compact format. Fragment spaces are useful both in similarity-based (2D) and structure-based (3D) de novo design applications. We present disconnection and filtering rules leading to several thousand unique, medium size fragments when applied to databases of druglike molecules. We evaluate alternative strategies to select subsets of these fragments, with the aim of maximizing the coverage of known druglike chemical space with a strongly reduced set of fragments. For these evaluations, we use the Ftrees fragment space method. We assess a diversity-oriented selection method based on maximum common substructures and a method biased toward high frequency of occurrence of fragments and find that they are complementary to each other.     

Is there a difference between leads and drugs? A historical perspective

To be considered for further development, lead structures should display the following properties: (1) simple chemical features, amenable for chemistry optimization; (2) membership to an established SAR series; (3) favorable patent situation; and (4) good absorption, distribution, metabolism, and excretion (ADME) properties. There are two distinct categories of leads: those that lack any therapeutic use (i.e., "pure" leads), and those that are marketed drugs themselves but have been altered to yield novel drugs. We have previously analyzed the design of leadlike combinatorial libraries starting from 18 lead and drug pairs of structures (S. J. Teague et al. Angew. Chem., Int. Ed. Engl. 1999, 38, 3743-3748). Here, we report results based on an extended dataset of 96 lead-drug pairs, of which 62 are lead structures that are not marketed as drugs, and 75 are drugs that are not presumably used as leads. We examined the following properties: MW (molecular weight), CMR (the calculated molecular refractivity), RNG (the number of rings), RTB (the number of rotatable bonds), the number of hydrogen bond donors (HDO) and acceptors (HAC), the calculated logarithm of the n-octanol/water partition (CLogP), the calculated logarithm of the distribution coefficient at pH 7.4 (LogD(74)), the Daylight-fingerprint druglike score (DFPS), and the property and pharmacophore features score (PPFS). The following differences were observed between the medians of drugs and leads: DeltaMW = 69; DeltaCMR = 1.8; DeltaRNG = DeltaHAC =1; DeltaRTB = 2; DeltaCLogP = 0.43; DeltaLogD(74) = 0.97; DeltaHDO = 0; DeltaDFPS = 0.15; DeltaPPFS = 0.12. Lead structures exhibit, on the average, less molecular complexity (less MW, less number of rings and rotatable bonds), are less hydrophobic (lower CLogP and LogD(74)), and less druglike (lower druglike scores). These findings indicate that the process of optimizing a lead into a drug results in more complex structures. This information should be used in the design of novel combinatorial libraries that are aimed at lead discovery.     

Synthesis of Complex Druglike Molecules by the Use of Highly Functionalized Bench‐Stable Organozinc Reagents

The reactivity of a representative set of 17 organozinc pivalates with 18 polyfunctional druglike electrophiles (informers) in Negishi cross‐coupling reactions was evaluated by high‐throughput experimentation protocols. The high‐fidelity scaleup of successful reactions in parallel enabled the isolation of sufficient material for biological testing, thus demonstrating the high value of these new solid zinc reagents in a drug‐discovery setting and potentially for many other applications in chemistry. Principal component analysis (PCA) clearly defined the independent roles of the zincates and the informers toward druggable‐space coverage.     

Synthesis and chemical diversity analysis of bicyclo[3.3.1]non-3-en-2-ones

Functionalized bicyclo[3.3.1]non-3-en-2-ones are obtained from commercially available phenols by a hypervalent iodine oxidation, enone epoxidation, epoxide thiolysis, and intramolecular aldol reaction sequence. Reaction optimization studies identified room temperature as well as microwave-mediated procedures, providing moderate to good yields (57-88%) in the thiophenol-mediated epoxide opening and intramolecular aldol reaction. In addition, the isolation of a key intermediate and in situ NMR studies supported the mechanistic hypothesis. The bicyclic ring products occupy novel chemical space according to ChemGPS and Chemaxon chemical diversity and cheminformatics analyses.     

Toxicity-indicating structural patterns

We describe a toxicity alerting system for uncharacterized compounds, which is based upon comprehensive tables of substructure fragments that are indicative of toxicity risk. These tables were derived computationally by analyzing the RTECS database and the World Drug Index. We provide, free of charge, a Java applet for structure drawing and toxicity risk assessment. In an independent investigation, we compared the toxicity classification performance of naive Bayesian clustering, k next neighbor classification, and support vector machines. To visualize the chemical space of both toxic and druglike molecules, we trained a large self-organizing map (SOM) with all compounds from the RTECS database and the IDDB. In summary, we found that a support vector machine performed best at classifying compounds of defined toxicity into appropriate toxicity classes. Also, SOMs performed excellently in separating toxic from nontoxic substances. Although these two methods are limited to compounds that are structurally similar to known toxic substances, our fragment-based approach extends predictions to compounds that are structurally dissimilar to compounds used in the training set.     

Regioselective synthesis and slow-release Suzuki-Miyaura cross-coupling of MIDA boronate-functionalized isoxazoles and triazoles

The efficient preparation of heterocycles with a range of substitutions ortho to heteroatoms remains as a challenge in organic synthesis, particularly relevant to the construction of druglike molecules due to the ubiquitous presence of such moieties in that chemical space. Modular installation of heterocyclic building blocks using Suzuki-Miyaura cross-coupling is a conceptually useful strategy to address this challenge, though this has historically been met with technical difficulty due to issues of inaccessibility and instability of the requisite heterocyclic boronates. Herein we report a mild and highly regioselective cycloaddition approach which affords convenient access to stable MIDA boronate-functionalized isoxazoles and triazoles and their subsequent efficient Suzuki-Miyaura cross-coupling. This methodology is then further applied to a set of druglike compounds in an efficient one-pot telescoped sequence in line with green chemistry principles.     

Guidelines for the Routine Application of the Peptide Hits Technique

A set of guidelines has been developed for using the peptide hits technique (PHT) as a semi-quantitative screening tool for the identification of proteins that change in abundance in a complex mixture. The dataset that formed the basis for these experiments was created using a cell lysate derived from the yeast Saccharomyces cerevisiae, spiked at various levels with serum albumin (BSA), and analyzed by LC/MS/MS and SEQUEST. Knowing that the level of only one protein (BSA) actually changed in the mixture allowed for the development and refinement of the necessary bioinformatics and statistical analyses, e.g., principal component analysis (PCA), normalization, and analysis of variation (ANOVA). As expected, the number of BSA peptide hits changed in proportion to the amount of BSA added to the sample. PCA was able to clearly distinguish between the spiked samples and the untreated sample, indicating that PCA may be able to classify samples, e.g., healthy versus diseased, in future experiments. The use of an endogenous "housekeeping" protein was found to be superior to the use of total hits for data normalization prior to analysis. An ANOVA based model readily identified BSA as a protein of interest, that is, one likely to be changing from amongst the background proteins, indicating that an ANOVA model may be able to identify individual proteins in target or biomarker discovery experiments. General guidelines based on these combined observations are set forth for future analyses and the rapid screening for candidate proteins of interest.     

A spectroscopic study of mechanochemically activated kaolinite with the aid of chemometrics

The study of kaolinite surfaces is of industrial importance. In this work we report the application of chemometrics to the study of modified kaolinite surfaces. DRIFT spectra of mechanochemically activated kaolinites (Kiralyhegy, Zettlitz, Szeg, and Birdwood) were analyzed using principal component analysis (PCA) and multicriteria decision making (MCDM) methods, PROMETHEE and GAIA. The clear discrimination of the Kiralyhegy spectral objects on the two PC scores plots (400-800 and 800-2030 cm(-1)) indicated the dominance of quartz. Importantly, no ordering of any spectral objects appeared to be related to grinding time in the PC plots of these spectral regions. Thus, neither the kaolinite nor the quartz, are systematically responsive to grinding time according to the spectral criteria investigated. The third spectral region (2600-3800 cm(-1)OH vibrations), showed apparent systematic ordering of the Kiralyhegy and, to a lesser extent, Zettlitz spectral objects with grinding time. This was attributed to the effect of the natural quartz on the delamination of kaolinite and the accompanying phenomena (i.e., formation of kaolinite spheres and water). With the MCDM methods, it was shown that useful information on the basis of chemical composition, physical properties and grinding time can be obtained. For example, the effects of the minor chemical components (e.g., MgO, K(2)O, etc.) indicated that the Birdwood kaolinite is arguably the most pure one analyzed. In another MCDM experiment, some support was obtained for the apparent trend with grinding time noted in the PC plot of the OH spectral region.     

荧光法检测化学战剂

化学战剂,包括神经性毒剂(如沙林、VX)和糜烂性毒剂(如芥子气),属于剧毒化学品,能够严重危害国家安全和环境安全.因此,针对各类化学战剂,开发简单、快速、可便携化、高灵敏度和高选择性的荧光检测技术具有重要的意义.本文综述了近年来国内外荧光法检测化学战剂的研究进展,并对该领域所面临的挑战和未来发展方向进行了总结和展望.     

New approach to molecular docking and its application to virtual screening of chemical databases

This paper describes the validation of a molecular docking method and its application to virtual database screening. The code flexibly docks ligand molecules into rigid receptor structures using a tabu search methodology driven by an empirically derived function for estimating the binding affinity of a protein-ligand complex. The docking method has been tested on 70 ligand-receptor complexes for which the experimental binding affinity and binding geometry are known. The lowest energy geometry produced by the docking protocol is within 2.0 A root mean square of the experimental binding mode for 79% of the complexes. The method has been applied to the problem of virtual database screening to identify known ligands for thrombin, factor Xa, and the estrogen receptor. A database of 10,000 randomly chosen "druglike" molecules has been docked into the three receptor structures. In each case known receptor ligands were included in the study. The results showed good separation between the predicted binding affinities of the known ligand set and the database subset.     

Structural covariance of graphs

Algebraic structures including multiple rank tensors, linear and non-linear operators are related to and represented with various types of graphs. Special emphasis is placed on linear operators e.g. on the Hibert space. A different graph represents the same operator depending on the basis frame used, in general non-orthonormal. All such graphs are shown to belong in one equivalence class and are termed structurally covariant. Crucial indices related to eigenvalues but invariant under any basis frame changes including non-orthonormal ones provide one way to characterize each class. A set of rules are given that allow one to find the graphs structurally covarinat with a given one and/or to deduce the class indices directly by simple pictorial manipulations on a graph. Applications in various fields including the quantum theory of molecules and reactions are indicated.     

Scaffold diversity of natural products: inspiration for combinatorial library design

Natural products contain scaffold structures that can be systematically exploited for the design of combinatorial compound libraries with druglike properties. We review approaches for scaffold identification, and compare properties and pharmacophoric features of drugs and natural products. In particular, an application of the self-organizing map technique is presented for natural product-derived compound and library design.     

A self-organizing algorithm for molecular alignment and pharmacophore development

We present a method for simultaneous three-dimensional (3D) structure generation and pharmacophore-based alignment using a self-organizing algorithm called Stochastic Proximity Embedding (SPE). Current flexible molecular alignment methods either start from a single low-energy structure for each molecule and tweak bonds or torsion angles, or choose from multiple conformations of each molecule. Methods that generate structures and align them iteratively (e.g., genetic algorithms) are often slow. In earlier work, we used SPE to generate good-quality 3D conformations by iteratively adjusting pairwise distances between atoms based on a set of geometric rules, and showed that it samples conformational space better and runs faster than earlier programs. In this work, we run SPE on the entire ensemble of molecules to be aligned. Additional information about which atoms or groups of atoms in each molecule correspond to points in the pharmacophore can come from an automatically generated hypothesis or be specified manually. We add distance terms to SPE to bring pharmacophore points from different molecules closer in space, and also to line up normal/direction vectors associated with these points. We also permit pharmacophore points to be constrained to lie near external coordinates from a binding site. The aligned 3D molecular structures are nearly correct if the pharmacophore hypothesis is chemically feasible; postprocessing by minimization of suitable distance and energy functions further improves the structures and weeds out infeasible hypotheses. The method can be used to test 3D pharmacophores for a diverse set of active ligands, starting from only a hypothesis about corresponding atoms or groups.